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  • 1
    Language: English
    Pages: 1 Online-Ressource (94 p.) , 21 x 29.7cm.
    Series Statement: OECD Education Working Papers no.148
    Keywords: Education
    Abstract: This report explores the relationships between mathematics teachers’ teaching strategies and student learning outcomes in eight countries, using information from the TALIS-PISA link database. First, the study seeks to understand the shaping of teaching strategies by examining the way teachers use different classroom practices and the prevalence of these strategies among teachers across schools and countries. As a result of this exploration, three teaching strategies are put forward: active learning, cognitive activation and teacher-directed instruction. Second, the report aims at identifying the teaching strategies that are positively associated with student skill acquisition. Third and finally, it analyses the contributions of the school and the classroom settings, the teacher background and beliefs, to the implementation of the teaching strategies found to be positively related to student learning outcomes. Results show that cognitive activation strategies and, to a lesser extent, active learning strategies, have a strong association with students’ achievement in mathematics. However, this association seems to be weaker in schools with socio-economically disadvantaged students. Also, teachers from the same school tend to share the same approach to teaching, which indicates that these teaching strategies are part of a “teaching culture” within the school. Teacher self-efficacy and teacher collaboration are shown to be the factors more often associated with the implementation of cognitive activation strategies and active learning. Following on from these findings, the paper concludes with a series of policy recommendations.
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  • 2
    Language: English
    Pages: 1 Online-Ressource (110 p.)
    Series Statement: OECD Education Working Papers no.201
    Keywords: Education
    Abstract: Large-scale surveys such as the Programme for International Student Assessment (PISA), the Teaching and Learning International Survey (TALIS), and the Programme for the International Assessment of Adult Competences (PIAAC) use advanced statistical models to estimate scores of latent traits from multiple observed responses. The comparison of such estimated scores across different groups of respondents is valid to the extent that the same set of estimated parameters holds in each group surveyed. This issue of invariance of parameter estimates is addressed in model fit indices which gauge the likelihood that one set of parameters can be used across all groups. Therefore, the problem of scale invariance across groups of respondents can typically be framed as the question of how well a single model fits the responses of all groups. However, the procedures used to evaluate the fit of these models pose a series of theoretical and practical problems. The most commonly applied procedures to establish invariance of cognitive and non-cognitive scales across countries in large-scale surveys are developed within the framework of confirmatory factor analysis and item response theory. The criteria that are commonly applied to evaluate the fit of such models, such as the decrement of the Comparative Fit Index in confirmatory factor analysis, work normally well in the comparison of a small number of countries or groups, but can perform poorly in large-scale surveys featuring a large number of countries. More specifically, the common criteria often result in the non-rejection of metric invariance; however, the step from metric invariance (i.e. identical factor loadings across countries) to scalar invariance (i.e. identical intercepts, in addition to identical factor loadings) appears to set overly restrictive standards for scalar invariance (i.e. identical intercepts). This report sets out to identify and apply novel procedures to evaluate model fit across a large number of groups, or novel scaling models that are more likely to pass common model fit criteria.
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